In recent years, various data-compressing methods have been proposed for receiving and transmitting between sensor nodes in a sensor network in which each communication terminal including a built-in vibration sensor acts as anode. For example, a compression method which uses Huffman codes allocates a short code to an information source alphabet (a symbol representing information) of a high probability (frequency) of appearance to encode, and can realize reversible compression which minimizes an average length. Further, compression methods such as pulse code modulation (PCM) and adaptive differential pulse code modulation (ADPCM) can enhance data compressibility even though compression is irreversible.
A technique of enhancing compressibility by combining a plurality of compression methods has also been studied. For example, not only compression methods which use Huffman codes but also compression methods which use alpha codes and gamma codes are prepared to select one of a plurality of compression methods and compress data, and add to compressed data a parameter indicating a type of the selected compression method. Thus, by combining a plurality of compression methods, it is possible to further enhance data compressibility (see JP 2012-134858 A and JP 2006-259937 A).
In recent network environment, Internet of things (IoT) and machine to machine (M2M) are advancing, and the amount of information transmitted from each sensor node tends to increase, and therefore a rise in a power consumption amount (electric consumption) of each sensor node is also expected. However, each sensor node is not necessarily disposed at a place at which an electric power infrastructure is built, and needs to be operated for a long period of time by using power of a built-in battery or button battery. Therefore, simply adopting a compression method of a high compressibility increases an arithmetic operation time for a compression process, and causes an increase in power consumption. Further, the same also applies to a technique of searching for an appropriate method from a plurality of compression methods, and, as a load of an arithmetic operation process for a search increases, a disadvantage in terms of electric power becomes greater. Meanwhile, adopting an irreversible compression method to reduce power consumption makes deterioration of information inevitable in return for adoption for this method.